Internship at Quantium

This summer, I worked on an exciting journey as a data analyst intern at Quantium. The internship was structured around a project-based approach, allowing me to dive deep into real-world retail analytics challenges.

First Steps: Onboarding and Initial Training

The internship began with an intensive onboarding process. I was introduced to the company's tools and methodologies, which included Python, Jupyter Notebook, and Power BI. The initial training sessions were instrumental in getting me up to speed with the data analysis techniques used at Quantium.

Data Preparation and Customer Analysis

My first task was to analyze customer purchasing trends to support a strategic recommendation for a category review. Here’s a glimpse into my workflow:

  1. Data Checks: Conducting data summaries, removing outliers, and correcting formats to ensure data integrity.
  2. Feature Engineering: Deriving new features such as pack size and brand name from the product descriptions.
  3. Customer Segmentation: Defining metrics to understand different customer segments and their spending behavior.

Experimentation and Uplift Testing

The second task involved evaluating a store trial for stores 77, 86, and 88. This required detailed analysis to determine the effectiveness of the trial. Key steps included:

  • Analyzing monthly sales data: total sales revenue, customer count, and average transactions per customer.
  • Creating a measure to compare trial stores with control stores.
  • Performing statistical tests to determine the significance of the results.

Analytics and Commercial Application

The final task was to generate insights and visualizations from transaction data and present actionable recommendations. This involved:

  • Using the output from previous tasks to create comprehensive charts and visualizations.
  • Developing a Power BI report that highlighted key insights and recommendations for the client.